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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

First experience of vectorizing electromagnetic physics models for detector simulation

The recent emergence of hardware architectures characterized by many-core or accelerated processors has opened new opportunities for concurrent programming models taking advantage of both SIMD and SIMT architectures. The GeantV vector prototype for detector simulations has been designed to exploit both the vector capability of mainstream CPUs and multi-threading capabilities of coprocessors including NVidia GPUs and Intel Xeon Phi. The characteristics of these architectures are very different in terms of the vectorization depth, parallelization needed to achieve optimal performance or memory access latency and speed. An additional challenge is to avoid the code duplication often inherent to supporting heterogeneous platforms. In this paper we present the first experience of vectorizing electromagnetic physics models developed for the GeantV project.

Amadio, G.↗
DOE OSTI2020

Enhancing Reliability of Classified Shipments Between the Nuclear Security Enterprise

The extent of this project, as related to by the Nuclear Security Enterprise (NSE), is related to the current shipping and logistical issues and optimization opportunities between several different NSE sites that are the basis of the enterprise. This current scope is part of every site’s, described as Design Agency (DA) and Production Agency (PA), normal operation to meet the needs and mission of the National Nuclear Security Administration (NNSA). The NSE has a broad mission scope encompassing several differing DA and PA sites to meet the NNSA’s mission. These sites require frequent interaction and shipments of material and items between one another in order to meet the mission needs of the enterprise. Currently, there is no methodology that integrates schedules, standards, orders, processes, and best practices to optimize transfers between the differing sites. A centralized location and standard shipping process will optimize and improve the systems behavior, reducing lag time and increasing throughput at sites today. Ultimately this project proposes a central logistical platform, tiered escalation process, and standardized shipping forms to reduce taxpayer costs to meet the NSE’s mission more efficiently. This increase in processing logistics and process accuracy of shipments will save the NSE, not only from a monetary value, but it will reduce the frustrations of individuals working these outdated and over processed systems to improve their quality of life.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

Electric Access System Enhancement (EASE): Assessment of a Distributed Energy Resource Management System for Enabling Dynamic Hosting Capacity

The Electric Access System Enhancement (EASE) project demonstrated a scalable, interoperable, and cost-effective means of integrating high penetration of distributed energy resources (DERs). The control architecture developed leveraged a Distributed Energy Resource Management System, Distribution System Operator for transacting energy, and 3rd Party DER Aggregator platform. The project identified ways to enhance the customer interconnection process to the grid and improve access to information from DERs and optimize the usage of DERs to provide energy services in a simulated day-ahead shadow market while maintain grid reliability. By integrating these capabilities into a scalable system of systems, the DSO can effectively balance DER generation and customer demand on the distribution network. This capability allows the grid to host more DER than traditionally possible on wires alone. Hosting more DER has the added benefit of supplying increased demand growth, sometimes beyond the capacity limits of the distribution network itself. This is known as a dynamic hosting capacity, which could help utilities manage the forecasted growth in electricity demand as California switch to electric vehicles and appliances. This could help to establish energy storage and PV generation as a “pseudo firm” generation resource mix if managed appropriately and provide sufficient resource adequacy for distribution capacity upgrade deferrals.

14 SOLAR ENERGY↗
DOE OSTI2025

Digital Twin Framework for PIP-II Linac: AI-Driven Multi-Scale Modeling from Ion Source to 800 MeV

The PIP-II linac will enable >1.2 MW beam power for DUNE, requiring unprecedented operational reliability across its warm front-end (RFQ, MEBT) and five distinct SRF sections operating at 162.5/325/650 MHz. We present a comprehensive digital twin framework uniquely combining a fully differentiable fast beam transport code with neural network surrogates trained on high-fidelity PIC simulations, capturing space charge and nonlinear dynamics beyond traditional envelope codes while achieving 10⁴ speedup at <1% accuracy. End-to-end differentiability enables gradient-based optimization across 500+ parameters simultaneously previously impossible with conventional tools while the model incorporates static/dynamic errors and serves as a virtual commissioning platform for diverse hardware integration. The framework facilitates reinforcement learning for pulsed/CW mode transitions, predictive maintenance through anomaly detection, and autonomous tuning algorithm development with real-time execution capability. Validation against physics simulations shows excellent agreement for the front-end, with initial results demonstrating potential for 30% commissioning time reduction and proactive fault mitigation, providing a scalable blueprint for operating next-generation high-intensity accelerators.

Pathak, Abhishek [Fermilab] (ORCID:000000021704208↗
DOE OSTI2025

Digital Twin Framework for PIP-II Linac: AI-Driven Multi-Scale Modeling from Ion Source to 800 MeV

The PIP-II linac will enable >1.2 MW beam power for DUNE, requiring unprecedented operational reliability across its warm front-end (RFQ, MEBT) and five distinct SRF sections operating at 162.5/325/650 MHz. We present a comprehensive digital twin framework uniquely combining a fully differentiable fast beam transport code with neural network surrogates trained on high-fidelity PIC simulations, capturing space charge and nonlinear dynamics beyond traditional envelope codes while achieving 10⁴× speedup at <1% accuracy. End-to-end differentiability enables gradient-based optimization across 500+ parameters simultaneously—previously impossible with conventional tools—while the model incorporates static/dynamic errors and serves as a virtual commissioning platform for diverse hardware integration. The framework facilitates reinforcement learning for pulsed/CW mode transitions, predictive maintenance through anomaly detection, and autonomous tuning algorithm development with real-time execution capability. Validation against physics simulations shows excellent agreement for the front-end, with initial results demonstrating potential for 30% commissioning time reduction and proactive fault mitigation, providing a scalable blueprint for operating next-generation high-intensity accelerators.

Pathak, Abhishek [Fermilab] (ORCID:000000021704208↗
DOE OSTI2015

The CARIBU EBIS control and synchronization system

The Californium Rare Isotope Breeder Upgrade (CARIBU) Electron Beam Ion Source (EBIS) charge breeder has been built and tested. The bases of the CARIBU EBIS electrical system are four voltage platforms on which both DC and pulsed high voltage outputs are controlled. The high voltage output pulses are created with either a combination of a function generator and a high voltage amplifier, or two high voltage DC power supplies and a high voltage solid state switch. Proper synchronization of the pulsed voltages, fundamental to optimizing the charge breeding performance, is achieved with triggering from a digital delay pulse generator. The control system is based on National Instruments realtime controllers and LabVIEW software implementing Functional Global Variables (FGV) to store and access instrument parameters. Fiber optic converters enable network communication and triggering across the platforms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Advanced Algal Biofoundries for the Production of Polyurethane Precursors [Abstract]

The collaboration between PNNL, LBNL, and UCSD will develop novel algae bioproduction platforms for the generation of polymer precursors. To achieve this, we will design and construct genetic tools for enhanced production of target chemicals. Biosensors will be developed to detect target chemical production. We will expand our knowledge of metabolic and regulatory systems that control or inhibit biosynthesis of the target molecules, and use this knowledge base to optimize production titers. Finally, we will integrate the knowledge gained from each activity to produce a set of the most promising production strains used to demonstrate the economic viability of producing polymer precursors in algal bioproduction platforms at scale under either heterotrophic or photosynthetic growth.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Interregional Transmission Operational Coordination (IRTOC)

This report presents a modeling and evaluation framework developed through the Inter-Regional Transmission Operational Coordination (IRTOC) project to study market-to-market (M2M) congestion management across day-ahead and real-time markets. The framework extends the Sienna platform through Sienna Decomposition, a multi-stage evaluation architecture that enables flexible representation of multiple regions and systematic assessment of alternative market coordination designs. Additional modeling capabilities include reserve deliverability constraints, High-Voltage Direct Current (HVDC) optimization for Alternating Current (AC) congestion management, and several real-time distributed coordination algorithms. Case studies using the RTS-GMLC test system and a large-scale Eastern Interconnection model demonstrate that the framework can evaluate alternative coordination structures and quantify their economic and operational impacts. The proposed framework provides a scalable platform for analyzing inter-regional coordination strategies in large-scale electricity markets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Genome-Scale Metabolic Model of Caldicellulosiruptor bescii Reveals Optimal Metabolic Engineering Strategies for Bio-based Chemical Production

The extremely thermophilic cellulolytic bacterium, Caldicellulosiruptor bescii , degrades plant biomass at high temperatures without any pretreatments and can serve as a strategic platform for industrial applications. The metabolic engineering of C. bescii , however, faces potential bottlenecks in bio-based chemical productions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Next-Generation Energy Technologies for Connected and Automated On-Road Vehicles (NEXTCAR) - Predictive Data-Driven Vehicle Dynamics and Powertrain Control: from ECU to the Cloud (Final Scientific/Technical Report)

This project developed and demonstrated a predictive, data-driven vehicle control system designed to improve energy efficiency and driving performance. The team created intelligent self-driving car technology that optimizes fuel and electricity use by proactively planning vehicle actions. By combining Level 4 autonomous driving capabilities with vehicle-to-everything (V2X) connectivity, the system enables vehicles to adjust speed and change lanes in response to traffic signals, surrounding vehicles, and road conditions, reducing unnecessary stops and delays. In testing, the system improved vehicle fuel economy by more than 30% and reduced travel time by approximately 10%, compared to a conventional adaptive cruise control baseline. These results demonstrate the technical effectiveness of using predictive, V2X-enabled strategies, such as traffic light timing and surrounding traffic awareness, to inform real-time vehicle powertrain control and driving behavior. Additionally, a supporting cloud platform was developed to provide dispatch and route recommendations as well as to log vehicle data, demonstrating the economic feasibility of this approach at the fleet level. By optimizing dispatching and routing operations, this technology enables electric fleet operators to use their vehicles more efficiently and reduce reliance on diesel backups, lowering both operating costs and energy consumption. Overall, this project’s technology advances the future of clean, energy-efficient transportation, enabling vehicles and fleets to reduce energy waste, cut costs, and lower emissions through intelligent automation and connectivity.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

An Improved Boosting to Amplify Signal with Isobaric Labeling (iBASIL) Strategy for Precise Quantitative Single-cell Proteomics

Mass spectrometry (MS)-based proteomics has great potential for overcoming the limitations of antibody-based immunoassays for antibody-independent, comprehensive, and quantitative proteomic analysis of single cells. Indeed, recent advances in nanoscale sample preparation have enabled effective processing of single cells. In particular, the concept of using boosting/carrier channels in isobaric labeling to increase the sensitivity in MS detection has also been increasingly used for quantitative proteomic analysis of small-sized samples including single cells. However, the full potential of such boosting/carrier approaches has not been significantly explored, nor has the resulting quantitation quality been carefully evaluated. Herein, we have further evaluated and optimized our recent boosting to amplify signal with isobaric labeling (BASIL) approach, originally developed for quantifying phosphorylation in small number of cells, for highly effective analysis of proteins in single cells. This improved BASIL (iBASIL) approach enables reliable quantitative single-cell proteomics analysis with greater proteome coverage by carefully controlling the boosting-to-sample ratio (e.g. in general <100×) and optimizing MS automatic gain control (AGC) and ion injection time settings in MS/MS analysis (e.g. 5E5 and 300 ms, respectively, which is significantly higher than that used in typical bulk analysis). By coupling with a nanodroplet-based single cell preparation (nanoPOTS) platform, iBASIL enabled identification of ~2500 proteins and precise quantification of ~1500 proteins in the analysis of 104 FACS-isolated single cells, with the resulting protein profiles robustly clustering the cells from three different acute myeloid leukemia cell lines. This study highlights the importance of carefully evaluating and optimizing the boosting ratios and MS data acquisition conditions for achieving robust, comprehensive proteomic analysis of single cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Thermodynamic Modeling and Optimization of the Copper Flash Converting Process Using the Equilibrium Constant Method

Based on the principle of multiphase equilibrium, a mathematical model of the copper flash converting process was established by the equilibrium constant method, and a computational system was developed with the use of MetCal software platform. The mathematical model was validated by comparing simulated outputs, industrial data, and published data. To obtain high-quality blister copper, a low copper content in slag, and increased impurity removal rate, the model was then applied to investigate the effects of the operational parameters [oxygen/feed ratio (R{sub OF}), flux rate (R{sub F}), and converting temperature (T)] on the product weights, compositions, and the distribution behaviors of impurity elements. The optimized results showed that R{sub OF}, R{sub F}, and T should be controlled at approximately 156 Nm{sup 3}/t, within 3.0 pct, and at approximately 1523 K (1250 °C), respectively.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Supporting Building Portfolio Investment and Policy Decision Making through an Integrated Building Utility Data Platform

The American Recovery and Reinvestment Act stimulus funding of 2009 for smart grid projects resulted in the tripling of smart meters deployment. In 2012, the Green Button initiative provided utility customers with access to their real-time1 energy usage. The availability of finely granular data provides an enormous potential for energy data analytics and energy benchmarking. The sheer volume of time-series utility data from a large number of buildings also poses challenges in data collection, quality control, and database management for rigorous and meaningful analyses. In this paper, we will describe a building portfolio-level data analytics tool for operational optimization, business investment and policy assessment using 15-minute to monthly intervals utility data. The analytics tool is developed on top of the U.S. Department of Energy’s Standard Energy Efficiency Data (SEED) platform, an open source software application that manages energy performance data of large groups of buildings. To support the significantly large volume of granular interval data, we integrated a parallel time-series database to the existing relational database. The time-series database improves on the current utility data input, focusing on real-time data collection, storage, analytics and data quality control. The fully integrated data platform supports APIs for utility apps development by third party software developers. These apps will provide actionable intelligence for building owners and facilities managers. Unlike a commercial system, this platform is an open source platform funded by the U.S. Government, accessible to the public, researchers and other developers, to support initiatives in reducing building energy consumption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Automated Nanoflow Two-Dimensional Reversed-Phase Liquid Chromatography System Enables In-Depth Proteome and Phosphoproteome Profiling of Nanoscale Samples

Two-dimensional reversed-phase liquid chromatography (2D RPLC) separations have enabled near-comprehensive proteome profiling of biological systems. However, large samples containing milligram amounts of protein are usually required due to the significant sample losses incurred during offline fractionation. The large sample requirements preclude the application of 2D RPLC to biological systems having sample availability in the nanogram to low-microgram range. To achieve in-depth proteomic studies of trace samples, we have developed an automated nanoflow 2D RPLC platform in which the first dimension high-pH fractionation was performed at 300 nL/min on a 75-µm i.d. capillary column.Each fraction was then fully transferred to a second-dimension nanoLC separation using an autosampler equipped with a custom-machined syringe. In addition to optimizing fractionation conditions, we found that the use of a plastic 96-well plate as collection device and the adding of n-Dodecyl ß-D-Maltoside (0.01%) in the collection buffer can significantly improve sample recovery. We have demonstrated the nanoflow 2D RPLC platform can achieve confident identifications of ~37,000–69,000 unique peptides, corresponding to ~5300–6900 protein groups using only 100 to 1000 ng of HeLa tryptic digest. Furthermore, by integrating phosphopeptide enrichment, the platform can identify as many as ~20,000 phosphopeptides from 100 µg of MCF7 protein digest. Because this platform is assembled from commercially available components, our approach can be readily adapted in other proteomics laboratories.

Mass spectrometry, multidimensional separations, n↗
DOE OSTI2015

Revealing the preferred interlayer orientations and stackings of two-dimensional bilayer gallium selenide crystals

Characterizing and controlling the interlayer orientations and stacking order of bilayer two-dimensional (2D) crystals and van der Waals (vdW) heterostructure is crucial to optimize their electrical and optoelectronic properties. The four polymorphs of layered gallium selenide (GaSe) that result from different layer stacking provide an ideal platform to study the stacking configurations in bilayer 2D crystals. Here, through a controllable vapor-phase deposition method we selectively grow bilayer GaSe crystals and investigate their two preferred 0° or 60° interlayer rotations. The commensurate stacking configurations (AA' and AB-stacking) in as-grown 2D bilayer GaSe crystals are clearly observed at the atomic scale and the Ga-terminated edge structure are identified for the first time by using atomic-resolution scanning transmission electron microscopy (STEM). Theoretical analysis of the interlayer coupling energetics vs. interlayer rotation angle reveals that the experimentally-observed orientations are energetically preferred among the bilayer GaSe crystal polytypes. Here, the combined experimental and theoretical characterization of the GaSe bilayers afforded by these growth studies provide a pathway to reveal the atomistic relationships in interlayer orientations responsible for the electronic and optical properties of bilayer 2D crystals and vdW heterostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Producing a glycosylating Escherichia coli cell factory: The placement of the bacterial oligosaccharyl transferase pglB onto the genome

Highlights: • Expressing pglB from the genome creates a “plug and play” E. coli strain for homogeneous recombinant glycoprotein production. • This engineered strain can increase glycosylation efficiency and overall glycoprotein titres. • Parallel Reaction Monitoring can simultaneously confirm glycan addition and quantify absolute glycoprotein titres. Although Escherichia coli has been engineered to perform N-glycosylation of recombinant proteins, an optimal glycosylating strain has not been created. By inserting a codon optimised Campylobacter oligosaccharyltransferase onto the E. coli chromosome, we created a glycoprotein platform strain, where the target glycoprotein, sugar synthesis and glycosyltransferase enzymes, can be inserted using expression vectors to produce the desired homogenous glycoform. To assess the functionality and glycoprotein producing capacity of the chromosomally based OST, a combined Western blot and parallel reaction monitoring mass spectrometry approach was applied, with absolute quantification of glycoprotein. We demonstrated that chromosomal oligosaccharyltransferase remained functional and facilitated N-glycosylation. Although the engineered strain produced less total recombinant protein, the glycosylation efficiency increased by 85%, and total glycoprotein production was enhanced by 17%.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Solvent Screening for Separation Processes Using Machine Learning and High-Throughput Technologies

As the chemical industry shifts toward sustainable practices, there is a growing initiative to replace conventional fossil-derived solvents with environmentally friendly alternatives such as ionic liquids (ILs) and deep eutectic solvents (DESs). Artificial intelligence (AI) plays a key role in the discovery and design of novel solvents and the development of green processes. This review explores the latest advancements in AI-assisted solvent screening with a specific focus on machine learning (ML) models for physicochemical property prediction and separation process design. Additionally, this paper highlights recent progress in the development of automated high-throughput (HT) platforms for solvent screening. Finally, this paper discusses the challenges and prospects of ML-driven HT strategies for green solvent design and optimization. To this end, this review provides key insights to advance solvent screening strategies for future chemical and separation processes.

Artificial intelligence↗
DOE OSTI2014

Copper oxide assisted cysteine hierarchical structures for immunosensor application

The present work describes the promising electrochemical immunosensing strategy based on copper (II) assisted hierarchical cysteine structures (CuCys) varying from star to flower like morphology. The CuCys having average size of 10 μm have been synthesised using L-Cysteine as initial precursor in presence of copper oxide under environmentally friendly conditions in aqueous medium. To delineate the synthesis mechanism, detailed structural investigations have been carried out using characterization techniques such as X-ray diffraction, transmission electron microscopy, and Fourier transform infrared spectroscopy. The electrochemical behaviour of self-assembled CuCys on gold electrode shows surface controlled electrode reaction with an apparent electron transfer rate constant of 3.38 × 10{sup −4 }cm s{sup −1}. This innovative platform has been utilized to fabricate an immunosensor by covalently immobilizing monoclonal antibodies specific for Escherichia coli O157:H7 (E. coli). Under the optimal conditions, the fabricated immunosensor is found to be sensitive and specific for the detection of E. coli with a detection limit of 10 cfu/ml.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗